Patents by Inventor Kevyn B. Collins-Thompson
Kevyn B. Collins-Thompson has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 9600585Abstract: A request can be received and a request reading level representation for the request can be inferred. In response to the request, the request reading level representation can be compared with one or more reading difficulty level representations for one or more response items. Also in response to the request, one or more indications of results of comparing the request reading level representation with one or more reading difficulty level representations for the one or more response items can be returned. The indication(s) may include a ranking of the response items. The ranking can be based at least in part on a request reading level representation for the query and reading difficulty level representations for the response items. The response item(s) may also be returned.Type: GrantFiled: February 6, 2015Date of Patent: March 21, 2017Assignee: Microsoft Technology Licensing, LLCInventors: Sebastian de la Chica, Kevyn B. Collins-Thompson, Paul N. Bennett, David Alexander Sontag, Ryen W. White
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Patent number: 9535995Abstract: Technologies are described herein that pertain to optimizing a ranker component for a risk-oriented objective. Various definitions of risk are described herein, wherein risk is based upon variance in performance scores assigned to the ranker component for respective queries in a data store. Additionally, risk is optionally based upon variance in relative performance of the ranker component versus a baseline ranker component.Type: GrantFiled: December 13, 2011Date of Patent: January 3, 2017Assignee: Microsoft Technology Licensing, LLCInventors: Paul N. Bennett, Kevyn B. Collins-Thompson, Lidan Wang
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Publication number: 20150154307Abstract: A request can be received and a request reading level representation for the request can be inferred. In response to the request, the request reading level representation can be compared with one or more reading difficulty level representations for one or more response items. Also in response to the request, one or more indications of results of comparing the request reading level representation with one or more reading difficulty level representations for the one or more response items can be returned. The indication(s) may include a ranking of the response items. The ranking can be based at least in part on a request reading level representation for the query and reading difficulty level representations for the response items. The response item(s) may also be returned.Type: ApplicationFiled: February 6, 2015Publication date: June 4, 2015Applicant: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Sebastian de la Chica, Kevyn B. Collins-Thompson, Paul N. Bennett, David Alexander Sontag, Ryen W. White
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Patent number: 8954423Abstract: A request can be received and a request reading level representation for the request can be inferred. In response to the request, the request reading level representation can be compared with one or more reading difficulty level representations for one or more response items. Also in response to the request, one or more indications of results of comparing the request reading level representation with one or more reading difficulty level representations for the one or more response items can be returned. The indication(s) may include a ranking of the response items. The ranking can be based at least in part on a request reading level representation for the query and reading difficulty level representations for the response items. The response item(s) may also be returned.Type: GrantFiled: September 6, 2011Date of Patent: February 10, 2015Assignee: Microsoft Technology Licensing, LLCInventors: Sebastian de la Chica, Kevyn B. Collins-Thompson, Paul N. Bennett, David Alexander Sontag, Ryen W. White
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Patent number: 8719249Abstract: One or more systems and/or techniques are provided for constructing a query classification index that can be used to classify a query into relevant categories. Where documents in an index are classified into one or more category predictions for a category hierarchy, classification metadata is generated for categories to which a document in the index has been classified. Further, the classification metadata is associated to the corresponding documents in the index. Additionally, a query of the index can be classified using the metadata associated to the documents in the index, and query results can be provided that are classified by the one or more categories identified by the classification of the query.Type: GrantFiled: May 12, 2009Date of Patent: May 6, 2014Assignee: Microsoft CorporationInventors: Paul N. Bennett, David Maxwell Chickering, Kevyn B. Collins-Thompson, Susan Dumais, Daniel J. Liebling
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Patent number: 8700544Abstract: A query processing system is described herein for personalizing results for a particular user. The query processing system operates by receiving a query from a particular user u who intends to find results that satisfy the query with respect to a topic Tu, the user being characterized by user information ?u. In one implementation, the query processing system then produces a generic topic distribution Prr(T|q) associated with the query that is germane to a population of generic users, as well as a user-specific query-dependent topic distribution Pr(Tu|q,?u) for the particular user. The query processing system then produces personalized results for the particular user based on Prr(T|q) and Pr(Tu|q,?u). The query processing system can use multiple techniques to produce Pr(Tu|q,?u), such as, in one approach, a discriminative learning approach.Type: GrantFiled: June 17, 2011Date of Patent: April 15, 2014Assignee: Microsoft CorporationInventors: David A. Sontag, Kevyn B. Collins-Thompson, Paul N. Bennett, Ryen W. White, Susan T. Dumais
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Publication number: 20130151495Abstract: Technologies are described herein that pertain to optimizing a ranker component for a risk-oriented objective. Various definitions of risk are described herein, wherein risk is based upon variance in performance scores assigned to the ranker component for respective queries in a data store. Additionally, risk is optionally based upon variance in relative performance of the ranker component versus a baseline ranker component.Type: ApplicationFiled: December 13, 2011Publication date: June 13, 2013Applicant: MICROSOFT CORPORATIONInventors: Paul N. Bennett, Kevyn B. Collins-Thompson, Lidan Wang
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Publication number: 20130060763Abstract: A request can be received and a request reading level representation for the request can be inferred. In response to the request, the request reading level representation can be compared with one or more reading difficulty level representations for one or more response items. Also in response to the request, one or more indications of results of comparing the request reading level representation with one or more reading difficulty level representations for the one or more response items can be returned. The indication(s) may include a ranking of the response items. The ranking can be based at least in part on a request reading level representation for the query and reading difficulty level representations for the response items. The response item(s) may also be returned.Type: ApplicationFiled: September 6, 2011Publication date: March 7, 2013Applicant: MICROSOFT CORPORATIONInventors: Sebastian de la Chica, Kevyn B. Collins-Thompson, Paul N. Bennett, David Alexander Sontag, Ryen W. White
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Publication number: 20120323828Abstract: A query processing system is described herein for personalizing results for a particular user. The query processing system operates by receiving a query from a particular user u who intends to find results that satisfy the query with respect to a topic Tu, the user being characterized by user information ?u. In one implementation, the query processing system then produces a generic topic distribution Prr(T|q) associated with the query that is germane to a population of generic users, as well as a user-specific query-dependent topic distribution Pr(Tu|q,?u) for the particular user. The query processing system then produces personalized results for the particular user based on Prr(T|q) and Pr(Tu|q,?u). The query processing system can use multiple techniques to produce Pr(Tu|q,?u), such as, in one approach, a discriminative learning approach.Type: ApplicationFiled: June 17, 2011Publication date: December 20, 2012Applicant: Microsoft CorporationInventors: David A. Sontag, Kevyn B. Collins-Thompson, Paul N. Bennett, Ryen W. White, Susan T. Dumais
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Publication number: 20120233140Abstract: A model generation module is described herein for using a machine learning technique to generate a model for use by a search engine. The model assists the search engine in generating alterations of search queries, so as to improve the relevance and performance of the search queries. The model includes a plurality of features having weights and levels of uncertainty associated therewith, where each feature defines a rule for altering a search query in a defined manner when a context condition, specified by the rule, is present. The model generation module generates the model based on user behavior information, including query reformulation information and user preference information. The query reformulation information indicates query reformulations made by at least one agent (such as users). The preference information indicates at extent to which the users were satisfied with the query reformulations.Type: ApplicationFiled: March 9, 2011Publication date: September 13, 2012Applicant: Microsoft CorporationInventors: Kevyn B. Collins-Thompson, Ni Lao